ArticleTranslational cancer research2020
Integrative analysis of mRNA, miRNA and lncRNA profiles reveals the commonness between bladder cancer and breast cancer.
Article in Translational cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Predicting disease associations based on the higher order structure of ceRNA networks.Briefings in bioinformatics · 2025Article
- Integrated analysis of coexpression and a tumor-specific ceRNA network revealed a potential prognostic biomarker in breast cancer.Translational cancer research · 2023Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUrinary bladder cancer (BLCA) and breast cancer (BRCA) are two cancers which are the most common cause of death. Recent studies have found that BLCA and BRCA shared commonness on many areas, such as biological mechanism, molecular subtypes and clinical stage. Therefore, a mature knowledge of BRCA can help highlight the treatment and prognosis of BLCA.
methodsTo address this issue, we performed a comprehensive integrative analysis to investigate the similarity between both cancers. Firstly, functional enrichment analysis based on differently expressed transcripts was performed. Secondly, PPI network analysis was performed to identify some hub genes in both cancers. Thirdly, the machine learning method was applied to construct cancer predictor. Finally, competing endogenous RNA (ceRNA) networks of both cancers were constructed by applying the integrated method.
resultsThe functional enrichment analysis showed that ECM-receptor interaction, Focal adhesion, PI3K-Akt signaling pathway were significantly pathways shared by BLCA and BRCA. From the PPI networks analysis, we identified some potential biomarkers shared by both cancers, such as CCNB1, CDC20, BUB2 and so on. The mRNA type and lncRNA type cancer predictor with good classifying performance were generated with machine learning approach, and some mRNA and lncRNA that contribute to cancer diagnostic were identified. By construct ceRNA networks, we identified some common cancer-associated ceRNA pairs, which may be helpful to uncover the relationship between two cancers.
conclusionsOur findings enhance the understanding of the various molecular signatures and commonalities shared by BLCA and BRCA, suggesting that BLCA may be particularly responsive to some treatments for BRCA.
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